Our foundation models leverage Helm.ai’s DNN innovations for accurate behavioral prediction and decision-making in autonomous vehicles. Using unsupervised training on large-scale real driving data, our models enhance accuracy and robustness by learning directly from real-world experiences.
Our models generate predicted video sequences that represent likely outcomes based on observed sensor data, enabling scalable and cost-efficient training and validation.
Our models produce multiple plausible future frame sequences and paths consistent with the observed data, providing a robust and flexible approach to predictive tasks in autonomous driving.
Our foundation models automatically learn subtle yet crucial aspects of urban driving, enabling more natural and effective autonomous navigation.
Explore Helm.ai’s AI software, foundation models, and AI-based development and validation tools.
